Efficient mining of top k-closed itemset in real time

Abstract

Analytics of Streaming data has been interesting and one of the profound research areas in the Data Science. Analysis and examination of real time data is one of the major areas of challenge in the BigData Analytics. One of the areas of research being mining of top k-closed frequent Itemsets in real time. Therefore an efficient algorithm MCSET(Mining closed itemsets) is proposed which uses Hash mapping technique to mine efficiently the closed itemsets. Experimental results shows that proposed algorithm has improved the scalability and improved the time efficiency compared to the existing closed association rule mining algorithm of data streams.